Customer Sentiment Analysis & Predictive Service Automation with Data 360

The client is a leading real estate developer specializing in luxury residential and commercial properties, with operations spanning construction, sales, collections, customer experience, and community management.

The client operated with a mature system of record, but customer relationships were scattered across disconnected channels.

• Fragmented Visibility: Email, WhatsApp, app activity, kiosk visits, and call histories were isolated, forcing teams to rediscover context from scratch.
• Reactive Service Triaging: Cases were routed strictly by queue order and complexity rather than customer value, sentiment trajectory, escalation risk, or agent fatigue.
• Absence of Early Warning Signals: Customer frustration, payment failures, and SLA breach risks were detected only after formal complaints were raised.
• Lack of Predictive Executive Insights: Department heads relied on historical, after-the-fact reports rather than forward-looking escalation or churn analytics.

We established a unified intelligence layer natively within Salesforce, integrating cross-channel signals into Data 360 and activating AI-driven automation via Agentforce:

• Unified Customer Profile: Configured identity resolution across phone, email, app login, and social handles, ingesting real-time signals from all seven channels into a 90-day timeline alongside calculated insights for Customer Lifetime Value, Engagement Score, and Interaction Frequency.
• AI Lead Scoring & Propensity Modeling: Extended lead scoring with behavioral engagement, interaction history, and sentiment signals, routing high-priority opportunities directly to appropriate Relationship Managers.
• Sentiment Analysis & Escalation Intelligence: Classified interactions across channels by sentiment (Neutral, Frustrated, Angry, Anxious, Satisfied) and intent, generating an Escalation Risk Score directly on the profile.
• Proactive Communication Engine: Implemented event-triggered and failure-driven outreach using Agentforce to generate personalized WhatsApp, email, and push notifications.
• Intelligent Case Routing & Workload Optimization: Rebuilt routing around issue complexity, customer value, risk score, agent skill, and agent fatigue score to keep high-risk cases out of general queues.

• Executive Visibility Dashboards: Deployed an Executive CX dashboard, a Critical Risk View for 24–48 hour SLA breach forecasts, and an AI Insights Panel for natural-language trend exploration.
  
   

  

• Salesforce Data 360: Ingests, harmonizes, and unifies cross-channel profiles with native calculated insights.
• Predictive Models: Drives lead propensity scoring and composite escalation-risk prediction.
• Agentforce: Orchestrates natural-language assistance, context-aware responses, and automated actions.
• API Integration Layer: Connects telephony/IVR, WhatsApp Business API, mobile app, kiosks, and social listening with sub-minute latency.
• Trust & Governance: Operates within Salesforce access controls, incorporating AI grounding, data protection, and auditability.

• Unified Single View: Unified profile views across email, contact center, WhatsApp, mobile app, kiosks, social media, and website within five months.
• 24% Conversion Lift: Increased lead-to-opportunity conversion through explainable, propensity-based prioritization.
• 42% Faster Risk Detection: Flagged customer frustration and escalation risks before formal complaints were submitted.
• 48% Reduced Inbound Contact: Decreased status-enquiry volume through automated, event-driven customer updates.
• Predictive Leadership Oversight: Replaced historical reporting with predictive frustration heatmaps and SLA breach forecasts.